Large language models such as ChatGPT and GPT-4 for patient-centered care in radiology

被引:4
|
作者
Fink, Matthias A. [1 ]
机构
[1] Univ Klinikum Heidelberg, Klin Diagnost & Intervent Radiol, Neuenheimer Feld 420, D-69120 Heidelberg, Germany
来源
RADIOLOGIE | 2023年 / 63卷 / 09期
关键词
Artificial Intelligence; Natural Language Processing; Machine Learning; Deep Learning; Patient-centred approach;
D O I
10.1007/s00117-023-01187-8
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Background: With the introduction of ChatGPT in late November 2022, large language models based on artificial intelligence have gained worldwide recognition. These language models are trained on vast amounts of data, enabling them to process complex tasks in seconds and provide detailed, high-level text-based responses. Objective: To provide an overview of the most widely discussed large language models, ChatGPT and GPT-4, with a focus on potential applications for patient-centered radiology. Materials and methods: A PubMed search of both large language models was performed using the terms "ChatGPT" and "GPT-4", with subjective selection and completion in the form of a narrative review. Results: The generic nature of language models holds great promise for radiology, enabling both patients and referrers to facilitate understanding of radiological findings, overcome language barriers, and improve the quality of informed consent discussions. This could represent a significant step towards patient-centered or person-centered radiology. Conclusion: Large language models represent a promising tool for improving the communication of findings, interdisciplinary collaboration, and workflow in radiology. However, important privacy issues and the reliable applicability of these models in medicine remain to be addressed.
引用
收藏
页码:665 / 671
页数:7
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